[BEAM-7739] Implement ReadModifyWriteState in Python SDK

examples/java/src/main/java/org/apache/beam/examples/complete/game/StatefulTeamScore2.java

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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.examples.complete.game;
+
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.MoreObjects.firstNonNull;
+
+import java.util.HashMap;
+import java.util.Map;
+import org.apache.beam.examples.common.ExampleUtils;
+import org.apache.beam.examples.complete.game.utils.GameConstants;
+import org.apache.beam.examples.complete.game.utils.WriteToBigQuery.FieldInfo;
+import org.apache.beam.examples.complete.game.utils.WriteWindowedToBigQuery;
+import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.PipelineResult;
+import org.apache.beam.sdk.coders.VarIntCoder;
+import org.apache.beam.sdk.extensions.gcp.options.GcpOptions;
+import org.apache.beam.sdk.io.gcp.pubsub.PubsubIO;
+import org.apache.beam.sdk.options.Default;
+import org.apache.beam.sdk.options.Description;
+import org.apache.beam.sdk.options.PipelineOptionsFactory;
+import org.apache.beam.sdk.state.StateSpec;
+import org.apache.beam.sdk.state.StateSpecs;
+import org.apache.beam.sdk.state.ReadModifyWriteState;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.MapElements;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TypeDescriptor;
+import org.apache.beam.sdk.values.TypeDescriptors;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.annotations.VisibleForTesting;
+import org.joda.time.Instant;
+
+/**
+ * This class is part of a series of pipelines that tell a story in a gaming domain. Concepts
+ * include: stateful processing.
+ *
+ * <p>This pipeline processes an unbounded stream of 'game events'. It uses stateful processing to
+ * aggregate team scores per team and outputs team name and it's total score every time the team
+ * passes a new multiple of a threshold score. For example, multiples of the threshold could be the
+ * corresponding scores required to pass each level of the game. By default, this threshold is set
+ * to 5000.
+ *
+ * <p>Stateful processing allows us to write pipelines that output based on a runtime state (when a
+ * team reaches a certain score, in every 100 game events etc) without time triggers. See
+ * https://beam.apache.org/blog/2017/02/13/stateful-processing.html for more information on using
+ * stateful processing.
+ *
+ * <p>Run {@code injector.Injector} to generate pubsub data for this pipeline. The Injector
+ * documentation provides more detail on how to do this.
+ *
+ * <p>To execute this pipeline, specify the pipeline configuration like this:
+ *
+ * <pre>{@code
+ * --project=YOUR_PROJECT_ID
+ * --tempLocation=gs://YOUR_TEMP_DIRECTORY
+ * --runner=YOUR_RUNNER
+ * --dataset=YOUR-DATASET
+ * --topic=projects/YOUR-PROJECT/topics/YOUR-TOPIC
+ * }</pre>
+ *
+ * <p>The BigQuery dataset you specify must already exist. The PubSub topic you specify should be
+ * the same topic to which the Injector is publishing.
+ */
+public class StatefulTeamScore2 extends LeaderBoard {
+
+  /** Options supported by {@link StatefulTeamScore}. */
+  public interface Options extends LeaderBoard.Options {
+
+    @Description("Numeric value, multiple of which is used as threshold for outputting team score.")
+    @Default.Integer(5000)
+    Integer getThresholdScore();
+
+    void setThresholdScore(Integer value);
+  }
+
+  /**
+   * Create a map of information that describes how to write pipeline output to BigQuery. This map
+   * is used to write team score sums.
+   */
+  private static Map<String, FieldInfo<KV<String, Integer>>> configureCompleteWindowedTableWrite() {
+
+    Map<String, WriteWindowedToBigQuery.FieldInfo<KV<String, Integer>>> tableConfigure =
+        new HashMap<>();
+    tableConfigure.put(
+        "team", new WriteWindowedToBigQuery.FieldInfo<>("STRING", (c, w) -> c.element().getKey()));
+    tableConfigure.put(
+        "total_score",
+        new WriteWindowedToBigQuery.FieldInfo<>("INTEGER", (c, w) -> c.element().getValue()));
+    tableConfigure.put(
+        "processing_time",
+        new WriteWindowedToBigQuery.FieldInfo<>(
+            "STRING", (c, w) -> GameConstants.DATE_TIME_FORMATTER.print(Instant.now())));
+    return tableConfigure;
+  }
+
+  public static void main(String[] args) throws Exception {
+
+    Options options = PipelineOptionsFactory.fromArgs(args).withValidation().as(Options.class);
+    // Enforce that this pipeline is always run in streaming mode.
+    options.setStreaming(true);
+    ExampleUtils exampleUtils = new ExampleUtils(options);
+    Pipeline pipeline = Pipeline.create(options);
+
+    pipeline
+        // Read game events from Pub/Sub using custom timestamps, which are extracted from the
+        // pubsub data elements, and parse the data.
+        .apply(
+            PubsubIO.readStrings()
+                .withTimestampAttribute(GameConstants.TIMESTAMP_ATTRIBUTE)
+                .fromTopic(options.getTopic()))
+        .apply("ParseGameEvent", ParDo.of(new ParseEventFn()))
+        // Create <team, GameActionInfo> mapping. UpdateTeamScore uses team name as key.
+        .apply(
+            "MapTeamAsKey",
+            MapElements.into(
+                    TypeDescriptors.kvs(
+                        TypeDescriptors.strings(), TypeDescriptor.of(GameActionInfo.class)))
+                .via((GameActionInfo gInfo) -> KV.of(gInfo.team, gInfo)))
+        // Outputs a team's score every time it passes a new multiple of the threshold.
+        .apply("UpdateTeamScore", ParDo.of(new UpdateTeamScoreFn(options.getThresholdScore())))
+        // Write the results to BigQuery.
+        .apply(
+            "WriteTeamLeaders",
+            new WriteWindowedToBigQuery<>(
+                options.as(GcpOptions.class).getProject(),
+                options.getDataset(),
+                options.getLeaderBoardTableName() + "_team_leader",
+                configureCompleteWindowedTableWrite()));
+
+    // Run the pipeline and wait for the pipeline to finish; capture cancellation requests from the
+    // command line.
+    PipelineResult result = pipeline.run();
+    exampleUtils.waitToFinish(result);
+  }
+
+  /**
+   * Tracks each team's score separately in a single state cell and outputs the score every time it
+   * passes a new multiple of a threshold.
+   *
+   * <p>We use stateful {@link DoFn} because:
+   *
+   * <ul>
+   *   <li>State is key-partitioned. Therefore, the score is calculated per team.
+   *   <li>Stateful {@link DoFn} can determine when to output based on the state. This only allows
+   *       outputting when a team's score passes a given threshold.
+   * </ul>
+   */
+  @VisibleForTesting
+  public static class UpdateTeamScoreFn
+      extends DoFn<KV<String, GameActionInfo>, KV<String, Integer>> {
+
+    private static final String TOTAL_SCORE = "totalScore";
+    private final int thresholdScore;
+
+    public UpdateTeamScoreFn(int thresholdScore) {
+      this.thresholdScore = thresholdScore;
+    }
+
+    /**
+     * Describes the state for storing team score. Let's break down this statement.
+     *
+     * <p>{@link StateSpec} configures the state cell, which is provided by a runner during pipeline
+     * execution.
+     *
+     * <p>{@link org.apache.beam.sdk.transforms.DoFn.StateId} annotation assigns an identifier to
+     * the state, which is used to refer the state in {@link
+     * org.apache.beam.sdk.transforms.DoFn.ProcessElement}.
+     *
+     * <p>A {@link ReadModifyWriteState} stores single value per key and per window. Because our pipeline is
+     * globally windowed in this example, this {@link ReadModifyWriteState} is just key partitioned, with one
+     * score per team. Any other class that extends {@link org.apache.beam.sdk.state.State} can be
+     * used.
+     *
+     * <p>In order to store the value, the state must be encoded. Therefore, we provide a coder, in
+     * this case the {@link VarIntCoder}. If the coder is not provided as in {@code
+     * StateSpecs.value()}, Beam's coder inference will try to provide a coder automatically.
+     */
+    @StateId(TOTAL_SCORE)
+    private final StateSpec<ReadModifyWriteState<Integer>> totalScoreSpec =
+        StateSpecs.readModifyWrite(VarIntCoder.of());
+
+    /**
+     * To use a state cell, annotate a parameter with {@link
+     * org.apache.beam.sdk.transforms.DoFn.StateId} that matches the state declaration. The type of
+     * the parameter should match the {@link StateSpec} type.
+     */
+    @ProcessElement
+    public void processElement(
+        ProcessContext c, @StateId(TOTAL_SCORE) ReadModifyWriteState<Integer> totalScore) {
+      String teamName = c.element().getKey();
+      GameActionInfo gInfo = c.element().getValue();
+
+      // ReadModifyWriteState cells do not contain a default value. If the state is possibly not written, make
+      // sure to check for null on read.
+      int oldTotalScore = firstNonNull(totalScore.read(), 0);
+      totalScore.write(oldTotalScore + gInfo.score);
+
+      // Since there are no negative scores, the easiest way to check whether a team just passed a
+      // new multiple of the threshold score is to compare the quotients of dividing total scores by
+      // threshold before and after this aggregation. For example, if the total score was 1999,
+      // the new total is 2002, and the threshold is 1000, 1999 / 1000 = 1, 2002 / 1000 = 2.
+      // Therefore, this team passed the threshold.
+      if (oldTotalScore / this.thresholdScore < totalScore.read() / this.thresholdScore) {
+        c.output(KV.of(teamName, totalScore.read()));
+      }
+    }
+  }
+}